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Customer Success Engineer

Trabajo disponible en: 08001, Barcelona, Cataluna, España
Empresa: Tamarind Intelligence
Tiempo completo puesto
Publicado en 2026-09-13
Especializaciones laborales:
  • TI/Tecnología
    Apoyo técnico, Ingeniero de IA
Rango Salarial o Referencia de la Industria: 60000 - 90000 EUR Anual EUR 60000.00 90000.00 YEAR
Descripción del trabajo

Customer Success Engineer --- Full-time

At Dialog, we are on a mission to build the best sales agent for e-commerce.

We believe generative AI is the perfect opportunity to bring the best of the in-store experience online:

  • extensive knowledge about the brand and its products
  • tailored advice based on previous orders

We launched on Shopify with Q&A on product pages. In 2026, we're scaling Dialog to new e-commerce engines and upgrading the experience with smarter qualification, an agent that runs across the entire store, and AI-powered search.

We wrote our first line of code in January 2024, started commercializing in September 2024, raised $4.4M in November 2025 and now have more than 100 paying customers.

The role

We are looking for a Customer Success Engineer to be the first line of defense for our customers' day-to-day technical issues, and to help us keep support quality high as we scale.

You will own our L1/L2 operations end-to-end across the technical topics that make Dialog work in production:
Shopify and Presta Shop integrations, configuration, front-end behavior, tracking and events, and AI-behavior questions.

  • L1 --- first line: triage, recurring requests, known fixes, and documented responses.
  • L2 --- second line: deeper reproduction and diagnosis, undocumented cases, before escalating to engineering.

The challenge as Dialog grows fast: keep support fast and high-quality while making sure it doesn't scale linearly with revenue, by resolving issues well and removing their root cause over time.

You will also investigate how our AI agent behaves in the real world: reading our AI agent traces end-to-end, spotting failure modes such as retrieval issues, tool errors, prompt gaps, or missing context, and translating what you find into concrete improvements for product and engineering.

And you will turn recurring problems into leverage: playbooks, runbooks, self-serve docs, and automation, including AI-assisted triage and responses, so the team and our clients stop hitting the same issue twice.

You will work closely with the Solution Engineering team, and the AM / Customer Success team. This role is for someone who enjoys solving concrete technical problems for customers, cares about doing things rigorously, and is genuinely excited to level up technically as the team grows.

Mission
  • Own L1/L2 operations end-to-end
  • You will be the go-to owner for incoming technical issues:
    Shopify and Presta Shop integrations, configuration, front-end behavior, and tracking/events. Your loop is reproduce → diagnose → fix (or apply a known workaround) → document, freeing senior engineers and AMs from repetitive work.
  • Enable customers and handle recurring asks
  • You will help customers and partners apply recommended fixes (docs, snippets, validation), support the onboarding of complex stores (custom themes, edge cases) without blocking sales, and take recurring client asks (reports, invoices, status updates) off the team's plate.
  • Drive faster time-to-resolution and keep the backlog under control
  • You will reduce median time-to-resolution on OPS tickets and keep the backlog healthy, escalating cleanly and with the right context whenever an issue needs engineering.
  • Industrialize support
  • You will default to fixing the class of problem, not the single ticket: when an issue repeats, you step back and solve it once for everyone. You will build and maintain runbooks and docs, automate recurring tasks, including with AI (agents, scripts, LLM-assisted triage and responses), and enable OPS and AM to self-serve on known cases so repeat load drops as we scale.
  • Investigate AI behavior with Langfuse
  • You will read traces end-to-end to understand client questions, context, tool usage, and failures, produce actionable conclusions (misconfig,…
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